Generative Agents: Interactive Simulacra of Human Behavior
Joon Sung Park
Stanford University
Stanford, USA
joonspk@stanford.edu
Joseph C. O’Brien
Stanford University
Stanford, USA
jobrien3@stanford.edu
Carrie J. Cai
Google Research
Mountain View, CA, USA
cjcai@google.com
Meredith Ringel Morris
Google DeepMind
Seattle, WA, USA
merrie@google.com
Percy Liang
Stanford University
Stanford, USA
pliang@cs.stanford.edu
Michael S. Bernstein
Stanford University
Stanford, USA
msb@cs.stanford.edu
Figure 1: Generative agents are believable simulacra of human behavior for interactive applications. In this work, we demonstrate
generative agents by populating a sandbox environment, reminiscent of The Sims, with twenty-five agents. Users can observe
and intervene as agents plan their days, share news, form relationships, and coordinate group activities.
ABSTRACT
Believable proxies of human behavior can empower interactive
applications ranging from immersive environments to rehearsal
spaces for interpersonal communication to prototyping tools. In
this paper, we introduce generative agents: computational software
agents that simulate believable human behavior. Generative agents
wake up, cook breakfast, and head to work; artists paint, while
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UIST ’23, October 29-November 1, 2023, San Francisco, CA, USA
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ACM ISBN 979-8-4007-0132-0/23/10.
https://doi.org/10.1145/3586183.3606763
authors write; they form opinions, notice each other, and initiate
conversations; they remember and reflect on days past as they plan
the next day. To enable generative agents, we describe an architec-
ture that extends a large language model to store a complete record
of the agent’s experiences using natural language, synthesize those
memories over time into higher-level reflections, and retrieve them
dynamically to plan behavior. We instantiate generative agents
to populate an interactive sandbox environment inspired by The
Sims, where end users can interact with a small town of twenty-five
agents using natural language. In an evaluation, these generative
agents produce believable individual and emergent social behav-
iors. For example, starting with only a single user-specified notion
that one agent wants to throw a Valentine’s Day party, the agents
autonomously spread invitations to the party over the next two
arXiv:2304.03442v2 [cs.HC] 6 Aug 2023